Training a convolutional neural network (CNN) to detect cars requires a large amount of labeled data. To support this application, a number of groups have taken an empirical approach, acquiring data with a specific camera or a small collection of cameras that were designed for consumer photography. These data sets are then labeled, either by people alone or with the help of specialized algorithms. Several of these datasets have been shared and serve as a resource for training [1]}, [2]}, [3]}, [4]}
